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Predicting Stock Returns and Volatility with Investor Sentiment Indices: A Reconsideration using a Nonparametric Causality-in-Quantiles Test

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, via Mersin 10, Northern Cyprus, Turkey and Department of Economics, University of Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Clement Kyei

    (Department of Economics, University of Pretoria)

Abstract

Evidence of monthly stock returns predictability based on popular investor sentiment indices, namely SBW and SPLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only SPLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality-in –quantiles model of Balcilar et al., (2015), in fact, both SBW and SPLS can predict stock returns and its volatility, with SPLS being a relatively stronger predictor of excess returns during bear and bull regimes, and SBW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2015. "Predicting Stock Returns and Volatility with Investor Sentiment Indices: A Reconsideration using a Nonparametric Causality-in-Quantiles Test," Working Papers 201575, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201575
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    Citations

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    Cited by:

    1. Marwane El Alaoui & Elie Bouri & Nehme Azoury, 2020. "The Determinants of the U.S. Consumer Sentiment: Linear and Nonlinear Models," IJFS, MDPI, vol. 8(3), pages 1-13, July.
    2. Tihana Škrinjarić & Branka Marasović & Boško Šego, 2021. "Does the Croatian Stock Market Have Seasonal Affective Disorder?," JRFM, MDPI, vol. 14(2), pages 1-16, February.

    More about this item

    Keywords

    Investor sentiment; stock markets; linear causality; nonlinear dependence; nonparametric causality; causality-in-quantiles;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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